Professional development of nurses in infection prevention and control: A scoping review of specialized training and competencies frameworks
Bibliographic record
Abstract
Background: Infection prevention and control (IPC) remain a challenge, particularly in the post-COVID-19 pandemic area. Currently, ongoing training appears to inadequately address the clinical needs of nurses. These training programs are seldom available online, and competency frameworks are poorly documented. The aim of this article is to map competency frameworks and continuous training content in IPC, including COVID-19, intended for nurses. Methods: A scoping review was conducted according to the Peters et al. method from the Joanna Briggs Institute. Results: A total of 42 articles were included, with the majority originating from the United States and the United Kingdom. Results were grouped into five major sections: 1) selection processes of the articles and their characteristics; 2) objectives of the identified articles; 3) characteristics and content of IPC training programs; 4) content of IPC competency frameworks; and finally, 5) digital IPC training during COVID-19. Conclusion: The findings from this scoping review could guide nursing education institutions and clinical settings in promoting ongoing training for nurses in IPC, potentially enhancing their advanced practice in this field. Contexte : La prévention et le contrôle des infections (PCI) demeurent un défi, particulièrement en temps de post-pandémie COVID-19. Actuellement, les formations continues ne semblent pas répondre suffisamment aux besoins cliniques des infirmières. Ces formations sont rarement accessibles en ligne tandis que les référentiels de compétences sont peu documentés. Le but de cet article est de cartographier les référentiels de compétences et les contenus de formation continue en PCI incluant la COVID-19, destinés aux infirmières. Méthodes : Une revue de la portée a été réalisée selon la méthode de Peters et al. du Joanna Briggs Institute. Résultats : Un total de 42 écrits a été retenu, dont la majorité provenaient des États-Unis et du Royaume-Uni. Les résultats ont été regroupés en cinq grandes sections : 1) processus de sélection des écrits et leurs caractéristiques, 2) buts des écrits recensés, 3) caractéristiques et contenus des formations en PCI, 4) contenus des référentiels de compétences en PCI, et finalement, 5) formations numériques en PCI durant la COVID-19. Conclusion : Les résultats issus de la présente revue de la portée pourraient guider les établissements d’enseignement des sciences infirmières, ainsi que les milieux cliniques afin de promouvoir la formation continue des infirmières en PCI, voire améliorer leur pratique avancée dans ce domaine.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.045 | 0.121 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.027 | 0.023 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".